# confint.lvmfit: Calculate confidence limits for parameters In kkholst/lava: Latent Variable Models

 confint.lvmfit R Documentation

## Calculate confidence limits for parameters

### Description

Calculate Wald og Likelihood based (profile likelihood) confidence intervals

### Usage

## S3 method for class 'lvmfit'
confint(
object,
parm = seq_len(length(coef(object))),
level = 0.95,
profile = FALSE,
curve = FALSE,
n = 20,
interval = NULL,
lower = TRUE,
upper = TRUE,
...
)


### Arguments

 object lvm-object. parm Index of which parameters to calculate confidence limits for. level Confidence level profile Logical expression defining whether to calculate confidence limits via the profile log likelihood curve if FALSE and profile is TRUE, confidence limits are returned. Otherwise, the profile curve is returned. n Number of points to evaluate profile log-likelihood in over the interval defined by interval interval Interval over which the profiling is done lower If FALSE the lower limit will not be estimated (profile intervals only) upper If FALSE the upper limit will not be estimated (profile intervals only) ... Additional arguments to be passed to the low level functions

### Details

Calculates either Wald confidence limits:

\hat{\theta} \pm z_{\alpha/2}*\hat\sigma_{\hat\theta}

or profile likelihood confidence limits, defined as the set of value \tau:

logLik(\hat\theta_{\tau},\tau)-logLik(\hat\theta)< q_{\alpha}/2

where q_{\alpha} is the \alpha fractile of the \chi^2_1 distribution, and \hat\theta_{\tau} are obtained by maximizing the log-likelihood with tau being fixed.

### Value

A 2xp matrix with columns of lower and upper confidence limits

### Author(s)

Klaus K. Holst

bootstrap{lvm}

### Examples


m <- lvm(y~x)
d <- sim(m,100)
e <- estimate(lvm(y~x), d)
confint(e,3,profile=TRUE)
confint(e,3)
## Reduce Ex.timings
B <- bootstrap(e,R=50)
B



kkholst/lava documentation built on Nov. 24, 2023, 9:31 a.m.